Abstract: When reducing radiation dose to healthy tissue near a target volume, a 4D motion model (52) of a target volume is generated during CT scan data acquisition. The target volume is tracked, and tracked target volume position information (43) is provided to a motion estimation tool (48). Motion parameter information (60) output from the motion estimation tool is linked to motion phases of the target volume indicated by CT scan data. A dynamic planned target volume (PTV) (64) that covers the target volume in each motion phase is generated and linked to tracked motion parameters for each respective motion phase. A radiation dose is delivered to the PTV for each motion phase using the linked motion parameters and real-time tracking information.

Abstract: A planning image memory stores a volume diagnostic image. A user inputs data defining clinical objectives including organs-at-risk with a user interface device. An auto-planning module generates a candidate treatment plan. A trade-off module having a processor evaluates the treatment plan against the clinical objectives. When one or more objectives is not met, the trade-off module performs a trade-off analysis to determine an effect on other clinical objectives and generates at least one trade-off treatment plan which more closely meets the not met objectives. The candidate and at least one trade-off plan are displayed on a display device and/or analyzed by the processor and a final treatment plan is selected from the at least one trade-off or candidate treatment plan.

Abstract: A planning image memory (14) stores a volume diagnostic image. A user inputs data defining clinical objectives including organs-at-risk with a user interface device (32). An auto-planning module (36) generates a candidate treatment plan. A trade-off module (38) having a processor evaluates the treatment plan against the clinical objectives. When one or more objectives is not met, the trade-off module (38) performs a trade-off analysis to determine an effect on other clinical objectives and generates at least one trade-off treatment plan which more closely meets the not met objectives. The candidate and at least one trade-off plan are displayed on a display device (30) and/or analyzed by the processor and a final treatment plan is selected from the at least one trade-off or candidate treatment plan.

Abstract: When reducing radiation dose to healthy tissue near a target volume, a 4D motion model (52) of a target volume is generated during CT scan data acquisition. The target volume is tracked, and tracked target volume position information (43) is provided to a motion estimation tool (48). Motion parameter information (60) output from the motion estimation tool is linked to motion phases of the target volume indicated by CT scan data. A dynamic planned target volume (PTV) (64) that covers the target volume in each motion phase is generated and linked to tracked motion parameters for each respective motion phase. A radiation dose is delivered to the PTV for each motion phase using the linked motion parameters and real-time tracking information.

Abstract: An engineering simulation tool uses boundary regions of proposed design modifications to a finite design element to assess the impact of those proposed design modifications. This tool allows a designer to incorporate a new design feature into a proposed model and generate simulated performance results for the proposed design without re-execution of finite element method.

Abstract: An engineering simulation tool uses boundary regions of proposed design modifications to a finite design element to assess the impact of those proposed design modifications. This tool allows a designer to incorporate a new design feature into a proposed model and generate simulated performance results for the proposed design without re-execution of finite element method.